module ProposalMatcherConfig where
import Instance

type Pref = Int

numAsWt x = fromInteger (toInteger x) :: Wt

reviewsEachProposal = 3 :: Int

prefIsExpert p = p <= 10
prefIsKnowledgeable p = p <= 20

prefIsBoring p = p > 15
prefIsVeryBoring p = p > 25

prefIsConflict p = p >= 40

-- For now this is absolute.  Later it might be proportional to a reviewer's
-- target load.
loadTolerance = 1 :: Int

-- Cost to overload by one review.
-- tx = 0 at target load, 1 at end of tolerance.
marginalLoadCost tx = 1000 + tx*1000 :: Wt

-- Cost to review a boring (or very boring) proposal.
-- lx = 0 at no load, 1 at target load.
marginalBoringCost lx = 1000 + lx*1000 :: Wt
-- Additional cost to review a very boring proposal.
marginalVeryBoringCost lx = 1000 + lx*1000 :: Wt

-- Cost to make a review.
-- I'm using quadratic cost functions as a first attempt.
assignmentCost pref = (numAsWt 10 + pref) ^ 2 :: Wt

-- Bonus for a first knowledgeable or expert review.
knowledgeableBonus = 1000 :: Wt

-- Bonus for an additional expert review.
expertBonus = 1000 :: Wt